I am not a doctor. I am a software developer who taught herself mobile development while working full-time and raising two kids. But I built a clinical simulation app used by medical students, and here is how I made sure it is actually clinically sound.
The credibility problem
When you don’t have an MD, you can’t rely on intuition or clinical experience. Every design decision has to be defensible, referenced, and auditable. So I built a framework, three audits that every case must pass before it goes live.
Audit 1: the evidence gate
Each case has “key tests,” the minimum a competent clinician would order before making the diagnosis. These are sourced from clinical guidelines: UpToDate, ESC, ACC, and standard textbooks.
Here is the rule: If a user guesses the correct diagnosis but skips key tests, they are blocked. The message? “Diagnosis correct, but dangerous process.”
This prevents lucky guessing. More importantly, it teaches that being right isn’t enough; the reasoning must be sound. You can’t treat what you haven’t confirmed.
Audit 2: the structure audit
Before publishing a case, I check the test list for problems:
- No duplicate tests revealing the same findings.
- Pricing reflects real-world costs proportionally.
- Every test reveals something; no useless options.
- Expensive distractors exist, tests that sound relevant but aren’t necessary.
Why does this matter? Redundancy confuses learners. Realistic pricing creates realistic trade-offs. And distractors teach restraint, the discipline to not order something just because it is available.
Audit 3: the budget calibration
This is where the real teaching happens. I use what I call the “Sniper vs. Shotgun” method.
First, I define the Sniper Workup, the minimum optimal set of tests a skilled clinician would order. Then I calculate that cost and add a 25 percent buffer. That becomes the budget.
The key constraint: Ordering the Sniper Workup plus one expensive distractor should exceed the budget. If it doesn’t, the budget is too generous and there is no real decision to make.
Here is a concrete example from a chronic subdural hematoma case:
- Sniper workup: Vitals, physical exam, head CT, coagulation studies, CBC, BMP, type and screen.
- Sniper cost: $635
- Buffer (25 percent): $160
- Final budget: $795
An MRI of the brain costs $800. Adding it breaks the budget, exactly as intended. The learner has to decide: Is it worth it, or can I reach the diagnosis without it?
Why constraints teach better than unlimited resources
A well-designed budget creates the same cognitive pressure a resident feels at 3 AM when they are weighing whether to wake the attending for an MRI approval. It is not about being cheap. It is about forcing the question: What do I actually need to know right now?
Too generous a budget means no constraint, no learning. Too tight means frustration. Calibrated correctly, the budget becomes invisible; learners simply feel the weight of their decisions.
The lesson
You don’t need unlimited resources to train good clinicians. You need structured limitations that reward efficient reasoning.
And you don’t need an MD to contribute to medical education. You need rigor, references, and a willingness to audit your own work ruthlessly. The methodology matters more than the credentials.
Helena Kaso is a software developer and independent creator focused on improving clinical reasoning education through technology. She is the founder of Diagnostic Studios and the creator of MedDiagnosis, a clinical reasoning simulator designed to teach diagnostic decision-making under real-world constraints such as limited time and limited budget. The app is available on both iOS and Android.
Based in Tirana, Albania, Kaso built MedDiagnosis to address a persistent gap in medical education. While trainees are taught what diagnoses to reach, they rarely practice how to choose efficiently among competing tests and pathways. Her work emphasizes cost-aware, constraint-based clinical reasoning that reflects real clinical environments.
